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All Journal Jurnal Mantik BERNAS: Jurnal Pengabdian Kepada Masyarakat
Ellisa Purba
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EDUKASI DAN PELATIHAN PEMANFAATAN TEKNOLOGI INFORMASI UNTUK IBU-IBU PKK DESA JATI BARU Wira Apriani; Nuraisana; Ellisa Purba
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol 1 No 4 (2020)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (291.738 KB) | DOI: 10.31949/jb.v1i4.469

Abstract

Pengabdian kepada masyrakat adalah salah satu hal wajib yang dilakukan oleh seorang dosen untuk menjalankan tri darma perguruan tinggi untuk itu seorang dosen diwajibkan lebih peduli dengan masyarakat masalah apa dan solusi apa yang ditawarkan untuk mengatasi masalah tersebut melalui penelitian dan pengabdian masyarakat, salah satu masalah yang ditemukan melalui observasi penulis adalah kurangnya pengetahuan tentang penggunaan komputer, smartphone dan internet oleh ibu-ibu PKK di Desa Jati Baru bahkan anak mereka lebih cakap dalam menggunakan hal tersebut sehingga anak mereka menggunakan komputer, smartphone dan internet tanpa pengawasan, selain itu perlunya mengedukasi cara mendapat keuntungan financial melaui internet dan sosial media serta mendapatkan pengetahuan tentang beretika dalam sosial media dan internet dan memahami konsep umum undang-undang informasi dan transaksi elektronik agar bijak dalam menggunakan internet.
Classification of Feasibility of Credit for Candidated CS Finance Debtors Using Naïve Bayes Method Nuraisana; Ellisa Purba
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1031.pp1885-1899

Abstract

CS Finance is one of the central financing institutions in the two-wheeler finance industry. CS Finance, which was founded in 2010 under the name PT Central Santosa Finance. The problem that is often faced is when conducting administrative assessments to determine the right prospective debtor's eligibility. We need a system that can assist CS Finance in determining the feasibility of prospective debtors quickly and precisely. The method used in this research is Naïve Bayes. The data processed is data of prospective debtors. The variables used have been determined based on four attributes, namely character, capacity, capital, and conditions; testing is carried out using Rapidminer software, and the accuracy of the Naïve Bayes algorithm for predicting the feasibility of prospective debtors based on training data shows good performance, namely 80%. Hence, it is feasible for use. To make it easier for users to predict prospective borrowers' creditworthiness, a creditworthiness classification system for prospective debtors has been created in CS Finance using the web-based naïve Bayes method.
Co-Authors Nuraisana Nuraisana Wira Apriani